Developmental shifts in computations used to detect environmental controllability

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Abstract

Accurate assessment of environmental controllability enables individuals to adaptively adjust their behavior-exploiting rewards when desirable outcomes are contingent upon their actions and minimizing costly deliberation when their actions are inconsequential. However, it remains unclear how estimation of environmental controllability changes from childhood to adulthood. Ninety participants (ages 8-25) completed a task that covertly alternated between controllable and uncontrollable conditions, requiring them to explore different actions to discover the current degree of environmental controllability. We found that while children were able to distinguish controllable and uncontrollable conditions, accuracy of controllability assessments improved with age. Computational modeling revealed that whereas younger participants' controllability assessments relied on evidence gleaned through random exploration, older participants more effectively recruited their task structure knowledge to make highly informative interventions. Age-related improvements in working memory mediated this qualitative shift toward increased use of an inferential strategy. Collectively, these findings reveal an age-related shift in the cognitive processes engaged to assess environmental controllability. Improved detection of environmental controllability may foster increasingly adaptive behavior over development by revealing when actions can be leveraged for one's benefit.

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APA

Raab, H. A., Foord, C., Ligneul, R., & Hartley, C. A. (2022). Developmental shifts in computations used to detect environmental controllability. PLoS Computational Biology, 18(6). https://doi.org/10.1371/journal.pcbi.1010120

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